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91 results on '"Švihlík, Jan"'

2. Smartphone Voice Calls Provide Early Biomarkers of Parkinsonism in Rapid Eye Movement Sleep Behavior Disorder.

Author

Illner, Vojtěch, Novotný, Michal, Kouba, Tomáš, Tykalová, Tereza, Šimek, Michal, Sovka, Pavel, Švihlík, Jan, Růžička, Evžen, Šonka, Karel, Dušek, Petr, and Rusz, Jan

Abstract

Background: Speech dysfunction represents one of the initial motor manifestations to develop in Parkinson's disease (PD) and is measurable through smartphone. Objective: The aim was to develop a fully automated and noise‐resistant smartphone‐based system that can unobtrusively screen for prodromal parkinsonian speech disorder in subjects with isolated rapid eye movement sleep behavior disorder (iRBD) in a real‐world scenario. Methods: This cross‐sectional study assessed regular, everyday voice call data from individuals with iRBD compared to early PD patients and healthy controls via a developed smartphone application. The participants also performed an active, regular reading of a short passage on their smartphone. Smartphone data were continuously collected for up to 3 months after the standard in‐person assessments at the clinic. Results: A total of 3525 calls that led to 5990 minutes of preprocessed speech were extracted from 72 participants, comprising 21 iRBD patients, 26 PD patients, and 25 controls. With a high area under the curve of 0.85 between iRBD patients and controls, the combination of passive and active smartphone data provided a comparable or even more sensitive evaluation than laboratory examination using a high‐quality microphone. The most sensitive features to induce prodromal neurodegeneration in iRBD included imprecise vowel articulation during phone calls (P = 0.03) and monopitch in reading (P = 0.05). Eighteen minutes of speech corresponding to approximately nine calls was sufficient to obtain the best sensitivity for the screening. Conclusion: We consider the developed tool widely applicable to deep longitudinal digital phenotyping data with future applications in neuroprotective trials, deep brain stimulation optimization, neuropsychiatry, speech therapy, population screening, and beyond. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society. [ABSTRACT FROM AUTHOR]

Published
2024
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4. Langerhans Islet Volume Estimation from 3D Optical Projection Tomography

Author

Švihlík, Jan, Kybic, Jan, Habart, David, Hlushak, Hanna, Dvořák, Jiří, Radochová, Barbora, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Chen, Chu-Song, editor, Lu, Jiwen, editor, and Ma, Kai-Kuang, editor

Published
2017
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23. Automated Analysis of Microscopic Images of Isolated Pancreatic Islets

Author

Habart, David, primary, Švihlík, Jan, additional, Schier, Jan, additional, Cahová, Monika, additional, Girman, Peter, additional, Zacharovová, Klára, additional, Berkov, Zuzana, additional, Kříž, Jan, additional, Fabryová, Eva, additional, Kosinová, Lucie, additional, Papáčková, Zuzana, additional, Kybic, Jan, additional, and Saudek, František, additional

Published
2016
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49. Point Spread Functions in Identification of Astronomical Objects from Poisson Noised Image.

Author

MOJŽÍŠ, Frantisek, KUKAL, Jaromir, and ŠVIHLÍK, Jan

Subjects
ASTRONOMICAL image processing, MATHEMATICAL functions, ASTRONOMICAL observations, POISSON'S ratio, IMAGE denoising
Abstract

This article deals with modeling of astronomical objects, which is one of the most fundamental topics in astronomical science. Introduction part is focused on problem description and used methods. Point Spread Function Modeling part deals with description of basic models used in astronomical photometry and further on introduction of more sophisticated models such as combinations of interference, turbulence, focusing, etc. This paper also contains a way of objective function definition based on the knowledge of Poisson distributed noise, which is included in astronomical data. The proposed methods are further applied to real astronomical data. [ABSTRACT FROM AUTHOR]

Published
2016
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